A Novel Technique for Reduction and Immobilization of Tibial Shaft Fractures: The Hammock
Bibliographic record
Abstract
Standard techniques for immobilization of a tibia shaft fracture in the emergency department in a long-leg splint can be cumbersome, technically difficult, and often requires the use of an assistant. We have developed a novel technique for the reduction and splinting of tibial shaft fractures, which uses a "hammock" constructed of stockinette, which allows a single consulting orthopaedic physician to rapidly reduce and place a long-leg plaster splint or cast on a patient. This technique was performed on 12 consecutive patients with a total of 12 tibial shaft fractures. Translation, angulation, and shortening of the fracture were documented in anteroposterior and lateral views of the injured tibia and these parameters were compared against values measured after the hammock technique was used to reduce and splint the fracture. Pre-"hammock" average values for fracture displacement in the anteroposterior plane for translation, angulation, and shortening were 10.5 mm (53.1%), 12.0°, and 9.4 mm, respectively. Post-"hammock" average values for fracture displacement in the anteroposterior plane for the same parameters were 8.7 mm (44.4%), 4.2°, and 7.9 mm, respectively. Pre-"hammock" average values for fracture displacement in the lateral plane for translation and angulation were 4.9 mm and 8.7°. Post-"hammock" average values for fracture displacement in the lateral plane for the same parameters were 4.9 mm and 2.0°, respectively. These results show that this technique is able to achieve the goals of fracture reduction and immobilization in a rapid fashion when help is not available.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".